NVIDIA WORTH TRILLIONS! Too Late to Buy NVDA Stock?

whether you put a piece of your paycheck into a retirement account every month or you actively pick your own stocks you should know that Nvidia is now the fourth biggest company in the S P 500 and the third biggest in the NASDAQ so if you're watching this video you're either already holding Nvidia stock in one way or another or you're seriously considering it but Nvidia stock just jumped up by a staggering 24 percent adding over 180 billion dollars to their market cap in a single day that's one of the biggest single day valuation increases in stock market history so in this episode I want to help you answer some important questions like did Nvidia stock just explode because of all the hype around generative Ai and chat GPT does Nvidia have any real competition and does their CEO really have their logo tattooed on his arm now that's commitment your time is valuable so let's get right into it when I first started buying Nvidia stock back in 2016 there weren't really any YouTube videos to help me understand the company or what I was getting myself into as an investor faster so I'd like to make that video for you now starting with the most important question first yes Jensen Wong really does have their logo tattooed on his arm and while that may seem like a silly detail to talk about at first glance one thing I always look for in my investments is that the leadership has real skin in the game no pun intended it's even better if the company is still led by its founder Jensen Wong is nvidia's CEO and co-founder and after 30 years he's still the company's fifth biggest shareholder owning 3.5 percent of the entire company that means he's got around a 33.5 billion dollar stake in Nvidia that's a big deal even if he starts selling some of his stock I wouldn't be too worried Jensen is 60 years old and him cashing in on his wife's work after three decades shouldn't be taken as a bad sign now let's talk about the company itself does Nvidia have any real competition did their stock just explode because of all the hype around chat GPT the best way to answer these questions is to really understand what the company does Nvidia is a full stack platform for Accelerated Computing that means they designed the hardware the different algorithms and acceleration libraries running on that hardware and a lot of the software applications that leverage those libraries nvidia's platform currently focuses on four major verticals gaming data center professional visualization and Automotive but as you'll see throughout the rest of this video nvidia's platform is useful well beyond those four markets just like Apple's app store or Microsoft's office ecosystem so let's start with gaming since that's where Nvidia really got its start many people don't realize just how much stuff nvidia's gaming segment includes beyond their gpus which I'll talk about more in a little bit they have the Nvidia Shield which is actually an entire family of consumer Android devices designed for streaming video and playing video games across a wide variety of form factors then there's GeForce now which is nvidia's cloud gaming service it lets users play PC games on Nvidia servers instead of their local machines for developers they have Nvidia studio and Nvidia Gameworks which are software Suites for Content creation that include visual effects physics simulation and artificial intelligence that are meant to run on nvidia's gpus one killer example of that artificial intelligence is dlss which stands for deep learning super sampling dlss uses deep learning and AI to improve the visual quality and performance of video games at a very high level what they do is they train a neural network to take in low resolution images from a video game and then predict what the pixels would be in a higher resolution version of that frame then when a player plays a game with dlss enabled the game can render at lower resolutions which costs fewer resources those low resolution frames are then fed to the trained AI model which predicts and presents the higher resolution version of the frame to the player in real time the big deal here is that predicting the high resolution frames is sometimes much faster than actually rendering them hopefully you can see how this kind of innovation can apply to much more than just video games just like the Innovations on their Hardware side at the heart of nvidia's gaming segment are their GeForce gpus there have been several lineups of the GeForce graphics cards over the decades built using different chip architectures the latest of which are Pascal Turing ampere and now Ada Lovelace so when you hear those terms in nvidia's presentations they're referring to these different blueprints for how the chips are built how different components interact and how information flows between those components the RTX series graphics cards are nvidia's latest lineup designed for high-end gaming desktops laptops and professional workstations those last two actually fall under professional visualization which I'll cover a little later in the video in terms of highlights for their gaming segment over this past quarter Nvidia announced the GeForce RTX 4060 family of gpus they launched the RTX 4070s they added dlss support to many more games and applications and they expanded GeForce now to include more than sixteen hundred games and now you know the basics of what all of that means as a result nvidia's gaming segment saw 2.24 billion dollars in revenue for the first quarter which is down 38 from a year ago but up 22 percent quarter over a quarter which indicates that two quarters ago was really the bottom for this segment gaming used to be nvidia's biggest segment by Revenue up until about 18 months ago but now that title belongs to their data center segment since their data center gpus power some of the fastest growing apps and services in history and speaking of fast growing apps MooMoo is a trading app built in Silicon Valley to help Advanced investors execute their strategies and they have a ton of great features to help you find great Investments at great prices like this awesome heat map that covers the performance of every industry at once for example I want to see how the top 50 U.S stocks in each industry have performed year to date now I can quickly see which Industries are way up and way down and click click on any industry to see all of its top stocks looks like semiconductor stocks are leading the market thanks to Nvidia and this tool makes that super easy to spot no wonder MooMoo has almost 20 million Advanced investors on their platform and right now MooMoo is giving away up to 20 free stocks each valued at up to two thousand dollars you just need to use my link in the description to download the app keep your account above a thousand dollars for at least 60 days and enjoy up to 20 free stocks but this offer ends very soon so make sure to get started today alright the special thing to understand about gpus is that they're useful for much more than just gaming gpus can process tons of data in parallel which is especially useful for both visual applications and crunching lots of numbers more and more applications across every Market are being powered by gpus from architecture and product design to simulations and streaming services in fact you're watching this video right now because of YouTube's video recommendation algorithm which runs on thousands and thousands of gpus inside their data centers not to mention the YouTube video service itself nvidia's data center segment includes a wide range of products and services designed for high performance Computing AI applications and big data processing let's start with our a100 tensor core gpus these are chips specifically designed for machine learning data analytics and high performance Computing AI training is where AI models learn to identify patterns from large amounts of labeled data like how gpt4 was trained on mountains of human-generated text Data inference is where a pre-trained model makes predictions on new unlabeled data that it hasn't seen before like when you give chat gbt a new prompt well nvidia's newer Hopper h100 data center chips are a massive step up from the a100s in terms of performance promising up to a 9x speed up in AI training and a whopping 30X speed up for AI inference and then there's Grace Grace is nvidia's First Data Center CPU it's an arm-based processor that's designed to handle tasks that require a lot of memory bandwidth such as large-scale scientific Computing AI training and data analytics according to Nvidia Grace can deliver 10 times the performance of normal CPUs when it comes to high performance Computing and AI workloads so we could see nvidia's grace chip start eating into Intel's server CPU market share which is still around 70 percent today so there's a lot of opportunity for NVIDIA in this space as more workloads shift to parallel Computing over time Nvidia can combine Grace and Hopper to form a single package called The Grace Hopper Superchip which can efficiently handle a wide range of tasks and workloads designed for CPUs gpus or both one thing that's always impressed me about nvidia's designs is that they can connect together to form more powerful systems at virtually any scale for example eight of these h100 chips can be connected to form a dgx h100 server system and if you combine nine dgx h100 services together you get a dgx pod which is actually a reference design that can be scaled up to offer AI services at the Enterprise level and Beyond but it doesn't stop there Nvidia can link 32 dgx pods together to create a super pod which provides around one extra flop of computing performance and Nvidia is currently linking 18 super pods together to build a super computer called EOS which will be about four times more powerful than the world's most powerful systems today nvidia's data center segment also includes their AI as a service through their tgx Cloud that's where customers can use each layer of their data center platform including their super computers their acceleration libraries they're pre-trained to generative AI models or Nvidia can help design custom models for Enterprise clients Nvidia showed record data center revenues of 4.28 billion dollars for the quarter which is up 14 year over year and 18 quarter over quarter which is another huge step up under earnings call Jensen Wong talked about how they're significantly ramping up production of the h100 gpus the grace CPUs the Superchip and the networking Hardware that lets them scale because there's been such a big surge in demand from their Enterprise Partners this is where we can really start answering the important questions from the start of this episode data Nvidia stock just explode because of all the hype around chat GPT I personally don't really think so I think it exploded because chat GPT and other generative AI tools are genuinely taking every industry by storm and there's a massive shift in workloads from CPUs to gpus and accelerated Computing as a result and because Nvidia doesn't really have any competition in this space today they're in the poll position to meet this very crazy but very real spike in demand just to be clear Amazon Microsoft and Google are all designing their own data center chips today but a lot of those chips have been aimed at reducing the Reliance on Intel and amd's CPUs not so much nvidia's gpus at least not yet so if another company wants to disrupt Nvidia I think they'd have to provide a huge step up in capability while maintaining a competitive price and to me that means they need massive scale to drive those costs down so this could mean maybe a new Amazon or Microsoft or Google data center GPU down the road but for now Nvidia is years ahead of other companies in this area and they've done a great job of being not just a chip designer but a full stack solution thanks to their algorithms acceleration libraries and the application is built on top of them for example their professional visualization and Automotive applications which I'll cover together since they were each less than five percent of nvidia's total revenue for the quarter applications like nvidia's Omniverse which is often described as the professional metaverse because it allows designers developers engineers and scientists to all work together in a shared virtual environment Omniverse is a platform designed to connect many other professional design tools across many different Industries together so a scene that was storyboarded with adobe's tools can be populated with 3D models built in SolidWorks or a 3D asset can be designed in CAD and then put into a scene in Unreal Engine so when any one of these tools gets a major upgrade almost every tool and project connected to the Omniverse can benefit from it in one way or another on top of that the Omniverse itself uses many of the other Nvidia technologies that we've covered to enable realistic Graphics physically accurate simulations materials behaviors and even lighting so while nvidia's Automotive segment will definitely benefit from these tools it's clearly built for much more than that not just car factories but all factories not just car design but all product design not just Road modeling and traffic simulation but all modeling and simulation and that kicks off a major feedback loop between nvidia's different business segments because as different Industries demand more and more of these kinds of software and services and video will need to keep designing better Hardware to support it and vice versa so hopefully this episode helped you understand the wide variety of AI hardware and software solutions that Nvidia makes how they all fit together to form a moat that's pretty hard to compete with and why nvidia's stock price spiked as a result of the mass adoption of AI tools like chat GPT but there's one more huge AI breakthrough that you need to know about so make sure to check out this episode next and if you feel I've earned it consider hitting the like button and subscribing to the channel that lets me know to put out more content like this either way thanks for watching and until next time this is ticker symbol U my name is Alex reminding you that the best investment you can make is in you

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Id: jraCU6kiAuU

Length: 13min 42sec (822 seconds)

Published: Sun May 28 2023